Cognitive style assessment among medical students: A step towards achieving meta-cognitive integration in medical education

Natl Med J India. Jul-Aug 2019;32(4):235-238. doi: 10.4103/0970-258X.291298.


Background: Knowledge of cognition and its regulation are important meta-cognitive activities, which are crucial for enhancement of learning. Their explicit teaching is meaningful and necessary yet seldom undertaken systematically in medical education programmes.

Methods: We aimed to identify the cognitive styles using the Alert Scale of Cognitive Style among our undergraduate students. Students were also sensitized about different cognitive styles, their implications in strategic learning and the importance of meta-cognitive approach in education. Feedback from students was obtained to understand their awareness, perspectives and relevance of meta-cognitive concepts.

Results: The intervention enhanced awareness of students about their own cognitive style and its implications to learning processes. The middle brain cognitive style was the most common (51.2%), followed by the right and the left brain cognitive styles (29.5% and 19.4%, respectively). A significant shift from the left towards the middle or the right cognitive style was observed in clinical years. No significant association was observed between a cognitive style and various variables such as age, gender and handedness.

Conclusion: Incorporation of meta-cognitive learning practices in medical education offers a basis for enhancing classroom teaching, thereby making it learner-centric. The study helped students in identifying the way they process information and in identifying their preferred methods of assimilating knowledge. Identification of cognitive diversity is a primary pedagogic act for improving competence in learning. Meta-cognitive skills can be harnessed to bring about consonance of the left, right and middle brain cognitive styles to achieve better learning outcomes.

MeSH terms

  • Cross-Sectional Studies
  • Education, Medical, Undergraduate*
  • Female
  • Humans
  • Learning / classification*
  • Male
  • Metacognition / classification*
  • Students, Medical / statistics & numerical data*